• Drug Discovery. Accelerated.



    It can take up to six years to build up a body of evidence to support a new drug candidate for commercial development. That’s a long time.


    At twoXAR, we are turning those years into minutes. Whether we are using your data to generate new drug candidates for a specific disease or assessing the efficacy of existing therapeutics, we can help.


    Using big data and patent-pending algorithms, we radically reduce the time it takes to find new drug candidates and assess their efficacy. Using our DUMA™ Drug Discovery platform we evaluate large public and proprietary datasets to identify and rank high probability drug-disease matches orders of magnitude faster than wet-lab approaches. These matches can be used to cross-validate clinical research, repurpose existing medicines, or identify novel drug candidates for further clinical testing.


    Our DUMA™ Drug Discovery Platform is a secure cloud-based solution that uses a patent-pending algorithm to find unanticipated associations between drug and disease. Its disease-agnostic approach includes four distinct stages: 

    1. Biological Data Extraction


    Sourcing, normalizing, and identifying disease signals in biological data sets


    2. Automated Model Generation


    Automatically generating a mathematical drug-disease model


    3. Feature Identification


    Extracting relevant factors from the model to guide drug classification


    4. Candidate Analysis


    Candidate analysis and classifying the efficacy of each drug using machine learning



    • Fast: typical engagement is from handshake to predictions in less than six months

    • Scalable: process data sets of any size in minutes using an elastic computing environment

    • Unbiased: predictions are based on statistical modeling – you control the amount of human input

    • Comprehensive: works with gene expression, protein-interaction, chemical structure, MOA, and clinical data, among others – it even handles noisy or incomplete assays

    • Agnostic: models work with any disease and have been tested on more than 20 diseases to date

    • User-friendly: predictions are summarized in easy-to-read PDF reports

    • No capex: service model requires no software license fees or local hardware installations

    Want to learn more about DUMA™ and how it worked in disease-specific case studies? Connect.


    Using our DUMA™ Drug Discovery Platform we are helping large and small R&D organizations evaluate target efficacy and expand drug pipelines. By working with twoXAR, you get the power of high-throughput screening without the time and capital expenses required performing traditional wet lab-based approaches or managing computational infrastructures. We can help you:

    Prioritize Existing Candidates


    Screen your existing candidates with additional evidence to support further investigation or early termination


    Perform Targeted Searches


    Configurable to focus on specific targets or classes of drugs






    Use custom parameters to find candidates and assess their efficacy for repositioning or new indications



    We have identified a number of candidates in therapeutic areas including autoimmunology, oncology, and neurology and are actively working with a number of leading patient advocacy, academic research, and biopharmaceutical organizations.


    If you are at an advanced stage with discovery candidates and need additional validation support or you are seeking entirely new targets, we can help. Connect.


    Some of the organizations we are collaborating with on drug discovery and candidate prioritization include:


    There are no positions currently available. Please connect with us for future opportunities.


    twoXAR's founders share more than a name, they share a commitment to disrupting the drug discovery process and accelerating the development of new medicines for rare and common health conditions.  They are supported by a team of experts in data science and systems biology and a network of advisers that includes biopharmaceutical industry and clinical research veterans.

    Andrew A. Radin

    CEO & Co-Founder


    Prior to co-founding twoXAR, Andrew held Chief Technology Officer roles at several early stage companies where he managed teams as large as a hundred technologists distributed around the world. Andrew  developed the company's proprietary algorithm and as Chief Executive Officer is focused on overall company strategy, product development and fundraising. 

    Andrew studied biomedical informatics in Stanford University's SCPD graduate program and holds Master of Science and Bachelor of Science degrees in computer science from Rochester Institute of Technology.


    Andrew M. Radin

    CBO & Co-Founder


    Andrew M. Radin formerly worked as an investor in venture and private equity funds and has designed, built, and managed several small organizations. Andrew co-founded a mobile platform startup while at MIT. As Chief Business Officer of twoXAR, Andrew is focused on validating the market, identifying customers, building the team, and fundraising.



    Andrew holds a Master in Business Administration degree from MIT Sloan, a Bachelor of Science degree in biochemistry and cell biology from UCSD, and a Bachelor of Arts degree in economics from UCSD.

  • twoXAR BLOG

    Recent Stories

    by: Andrew M. Radin
    Chief Business Officer, twoXAR


    The short-list for the annual Arthur C. Clarke Award was recently announced and it reminded me of a post we did last fall on augmentation vs. automation. Clarke is a British science fiction writer who is famous for being the co-screenplay writer (with Stanley Kubrick) of the 1968 film 2001: A Space Odyssey. He is also known for the so-called Clarke’s Laws, which are three ideas intended to guide consideration of future scientific developments... read post here.

    Guest post by Marina Sirota, PhD, twoXAR Advisor and Assistant Professor, UCSF Institute for Computational Health Sciences


    Earlier this month, Andrew A. Radin and I had the opportunity to attend a community outreach meeting at UC Irvine hosted by the NIH Libraries of Cellular Signatures (LINCS) consortium. It was a great and diverse community gathering of drug discovery researchers from academia, biopharma, startups, consulting companies and government funding agencies. For anyone interested in listening to the talks, some of them have been posted on YouTube.


    The focus of day one was to review the progress to date on collaborations among researchers spearheading projects that are exploring... read post here.

    See full blog at: medium.com/@twoXAR


    We’d love to connect with partners, future team members, and other computational biology folks. Contact us to arrange a meeting.

    221 Forest Ave
    Palo Alto,CA 94301
    (650) 382-2605